Investigating The Impact of Covid-19 on Individuals of Particular Race and Age Groups

Hillary Chen (), Emma Hong (), Julia Kharchenko () , Truc Quynh Nguyen (TQ) ()

Autumn 2022
INFO-201: Technical Foundations of Informatics - The Information School - University of Washington
Code Name: pillowtalk

Introduction

Covid-19 was declared a global pandemic on March 11th of 2020. At that point, there were already around 110,000 confirmed cases in 110 countries. Research showed that China had the first confirmed case. After that, there were confirmed cases in Iran, Italy, and South Korea. Shortly after, there was a major outbreak in cases all around the world. Covid-19 has affected everyone on earth. Whether it be directly or indirectly. Research shows that as of October, 10,2020, more than 7.7 million people across all the states of the US have tested positive for the virus. With that, the New York Times’s database showed that at least 213,876 people have passed away due to the virus in the United states. Covid-19 has been taking lives on a large scale and it makes us wonder, do different social identities play a role?

Keywords

Covid-19, Race, Age, Pandemic, Deaths, Cases

Abstract

We aim to address the question of how the Covid-19 pandemic has affected individuals of different races and ages, and how those two variables intersect. Such a question is important because it investigates how Covid-19 has disproportionately affected individuals of specific backgrounds, and because resulting correlations between the data can be used to assist individuals who are statistically prone to being impacted by the virus. Our project uses continually updated data provided by the Centers for Disease Control and Prevention to investigate and identify possible intersections between these two variables.

Problem Domain

Sociotechnical Situation and Project Framing: The Covid-19 pandemic has impacted individuals throughout the United States since early 2020, affecting people of all ages, races, ethnicities, sexes, etc, but not always equally. Research, such as this New York Times article on “Covid and Race,” indicates that Black Americans and Latinos have been disproportionately affected by the pandemic in comparison to their White counterparts in the United States. Similarly, this New York Times article on “Covid and Age,” indicates that the elderly are more likely to be hospitalized or die from the virus, whereas young children are shown to be less susceptible. The sudden nature of the pandemic has also created limitations in the criteria for Covid data, such as seen in this brief on “Covid 19 in children and adolescents,” which shows how hospitals throughout the United States have different criteria for what constitutes a case of Covid-19. This project will specifically investigate how Covid-19 has affected different age and race groups within the United States, as it is important to identify the inequalities which make certain groups more susceptible to the harms of the virus.

Human Values: The human values related to this project are the physical well-being of individuals throughout the United States, and to identify ways in which the health of individuals can be preserved despite the threat of a pandemic virus.

Direct and Indirect Stakeholders: Direct Stakeholders: Individuals who have obtained Covid-19 and been put into life-threatening situations because of the virus. Other direct stakeholders include hospital staff, nurses, educators, and any other professions who have been in contact with the virus while attempting to help others who have contracted it. Indirect Stakeholders: The indirect stakeholders are people who have not yet contracted Covid-19, but who are at risk of contracting it. Likewise, people who report on the pandemic and share information regarding the virus may benefit from the research which correlates population demographics and the impact of the virus.

Harms and Benefits: Benefits: Our data can be used to increase awareness in regards to which age and race demographics are most susceptible to the Covid virus. People who view this data can take preventive measures to ensure they don’t contract the virus, or can use the data to lessen the inequalities that exist between groups who have been impacted by Covid-19. Harms: All our datasets are from the CDC, and while the organization is regarded as reliable, there is a lack of variability in the data collected. The data by the CDC may also have different metrics than other organizations or sites, and therefore may face difficulties when compared to other Covid-related data.

Research Questions

Our three research questions are: - How has the Covid-19 pandemic affected individuals belonging to a specific age group? - How has the Covid-19 pandemic affected individuals belonging to a specific race? - Is there a correlation between race and age in concern to the Covid-19 pandemic, specifically in individuals who have been disproportionately affected by the virus?

The widespread impact of the Covid-19 pandemic has made it clear that individuals of all races and ages have been affected by the virus. Preliminary research suggests that in each category certain groups of individuals have been affected by the pandemic more than others. In regards to race, research indicates that Black Americans, Asian Americans, and Latinos have been disproportionately affected by the virus in comparison to White Americans. Likewise, research shows that the elderly are more susceptible to the virus than younger age demographic groups. Our research questions are centered around confirming whether the trends listed above are true, and to investigate the intersectionality that may exist between the categories of race and age in concern to the Covid-19 pandemic. We will look at case and death counts to measure which race and age groups have been most affected by the virus.

Dataset

We have collected three datasets for our project, each relating to one of our research questions. The dataset titled “Covid-19 Deaths by County, Race, and Hispanic Origin” answers the question of how Covid has affected individuals belonging to a specific race, the dataset titled “Covid-19 Deaths by Sex and Age” answers the question of how Covid has affected individuals belonging to a specific age group, and the dataset titled “Covid-19 Deaths by Region, Race, and Age” will help correlate the variables of race and age. We aim to compare these datasets by joining them by the variable of “date.” All of the datasets are continually updating, with the earliest dataset providing data back to May 1, 2020, and the others providing data from February 10, 2021, and June 24, 2021. All of our chosen datasets have been taken from the Center for Disease Control and Prevention website, or the CDC. We found all of our datasets by searching through the CDC website, typing key phrases into the search bar such as “Covid and Age” or “Covid and Race.” The specific data featured in each dataset has been collected by the National Center for Health Statistics, or the NCHS. Each dataset was created with the intention of helping provide the public easily accessible information about the Covid-19 pandemic in the form of raw statistical data. The NCHS collects the data included in each of these datasets by reviewing death certificate submissions. When death certificates are created they are submitted to the National Vital Statistics System, a system within the NCHS, which tabulates data from the certificate, including cause of death, comorbid conditions, an individual’s race, ethnicity, and the place of death. While the data collected by the NCHS is reliable, there is a 1-2 week delay in the NCHS counts due to delays in the submission system. These delays can come from states reporting deaths at different times, waiting for death-related test results, and in-person processing for Covid-19 deaths, as opposed to an automatic processing system. NCHS data also reports on provisional deaths only, and therefore may differ from data reported by other media sources. The CDC is regarded as a trustworthy and reliable scientific organization. The CDC uses peer review systems to verify collected data and scientific reports, and requires that all reports specify the procedures, methods, and errors that are involved in their data collection system.

Covid Table

Limitations

We might need to address that even if one is a part of these factors in the dataset, that does not mean that they have to panic. The goal of this project is to spread awareness and knowledge. Resulting in the possibility of changing one’s mindset on the pandemic. And also a possibility of changing their lifestyle in order to protect themselves and those that they love. Our project has the goal of reaching those who don’t know that they might have a higher possibility of being affected by Covid-19.

Expected Implications

With the results from the dataset, we hope that it helps spread awareness and knowledge. The pandemic has caused an uproar and has made the world wonder who are all the numbers on the charts titled “ covid deaths “. We want this information to reach direct and indirect stakeholders so they are more aware of what is happening and who is more likely to be affected. While reaching normal citizens, we also know that it reaches the policy makers. Policy makers have the ability to come up with small restrictions that would keep different individuals safe from the virus.

Dynamic Paragraph

We found that the age group with the least COVID deaths was 18-29 years. The age group with the most COVID deaths was 85 years and over. In terms of race, the group with the least COVID deaths turned out to be Non-Hispanic Native Hawaiian or Other Pacific Islander, while the group with the most COVID deaths was 85 years and over. Looking at the intersection of race and age, the racial group with the least deaths within the age group with the least deaths was Non-Hispanic Black.

Aggregate Table

# Age Group Covid Deaths by Age Percent Covid Deaths by Age Race Group Covid Deaths by Race Percent Covid Deaths by Race
1 0-17 years NA 0.0137602 Non-Hispanic White 2789044 0.7844225
2 18-29 years 26656 0.0370799 Non-Hispanic Black 599284 0.1710880
3 30-39 years 76256 0.0711354 Non-Hispanic American Indian or Alaska Native 46388 0.0827805
4 40-49 years 178940 0.1127300 Non-Hispanic Asian 133340 0.0404209
5 50-64 years 781492 0.1224238 Non-Hispanic Native Hawaiian or Other Pacific Islander 8900 0.0259211
6 65-74 years 969900 0.1246472 Hispanic 664864 0.1340704
7 75-84 years 1106608 0.1190618 NA NA NA
8 85 years and over 1124884 0.1036245 NA NA NA


In order to display the most important aspects of our data, we created an aggregated table of information that can be used to answer our initial research questions. This chart includes the two key variables we studied for this project - Age Group and Race - and how each group has been impacted by COVID. By filtering through our Age dataset, we calculated the amount of COVID Deaths and the percentage of deaths due to COVID for each selected age group. Likewise, we calculated the amount of COVID deaths and percentage of deaths due to COVID for each selected race by filtering through our Race dataset. In looking at this table, it can be easily observed that older age groups had greater amounts of COVID deaths, and that Non-Hispanic White individuals had the most amount of COVID deaths for any racial group.

Chart 1: Race and Age


We included a stacked bar chart detailing the racial background of those who died from COVID-19 per age group to identify the intersectionality between many marginalized groups when it comes to COVID-19 related deaths (e.g. how Hispanic milennials compare to the Black elderly population). By creating this chart, we can see that the older a person is, the more likely they are to die from COVID-19, and that the proportion of those dying from COVID-19 who are Non-Hispanic White are larger than other groups, likely because they make up a larger population as a whole. However, Hispanic and Non-Hispanic Black individuals tend to die from COVID-19 in larger proportions at slightly younger ages e.g. from 50-64 years, which is an interesting feature to look into and analyze further.

Chart 2: Race

We made a pie chart in order to see how different races has been affected by COVID-19. By the results of this visual, we were able to find out that Non-Hispanic White group made up 84.7% of this pie chart. This means that they were the most affected by COVID-19 versus other races. By making a pie chart, we were visually able to see the data as a fractional part of a whole which can be a straight forward and effect communication tool for even an uninformed reader.

Chart 3: Age


We included a standard bar chart to examine the age groups of individuals who died from COVID-19. In looking at this chart, we can understand that older age groups, specifically between 74-85 years old and 85 years or older, were much more susceptible to COVID-19, and likewise more likely to die from the virus. In opposition, younger age groups were less impacted by the virus, with adolescents and children in particular having almost no deaths in comparison to the older age groups.

References